Modernizing quality management with formal languages and neural networks.
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| Title: | Modernizing quality management with formal languages and neural networks. |
|---|---|
| Authors: | Utepbergenov, Irbulat1 i.utepbergenov@aues.kz, Toibayeva, Shara1 sh.toibaeva@aues.kz |
| Source: | International Journal of Electrical & Computer Engineering (2088-8708). Aug2025, Vol. 15 Issue 4, p4031-4042. 12p. |
| Subjects: | Formal languages, Artificial neural networks, Automation, Total quality management, Sustainability, Regulatory compliance, Information networks, Sustainable development |
| Abstract: | This paper explores the integration of formal languages and neural networks into quality management systems to enhance efficiency and sustainability. Formal languages standardize regulatory documents, reducing misinterpretation and simplifying modification, contributing to innovative infrastructure (SDG 9). Recurrent neural networks (RNNs) automate document analysis, non-conformance detection, and decision-making, improving production efficiency and promoting responsible consumption (SDG 12). Automation in quality management reduces costs, enhances competitiveness, and aligns with decent work and economic growth (SDG 8). Standardizing documentation and automating quality control enhance workforce competencies and support quality education (SDG 4). These technologies strengthen regulatory transparency, reduce legal risks, and improve governance, supporting strong institutions (SDG 16). The proposed approach fosters sustainable development through digitalization and automation, ensuring efficiency, innovation, and compliance with environmental and social standards. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Electrical & Computer Engineering (2088-8708) is the property of Institute of Advanced Engineering & Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 187706914 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Modernizing quality management with formal languages and neural networks. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Utepbergenov%2C+Irbulat%22">Utepbergenov, Irbulat</searchLink><relatesTo>1</relatesTo><i> i.utepbergenov@aues.kz</i><br /><searchLink fieldCode="AR" term="%22Toibayeva%2C+Shara%22">Toibayeva, Shara</searchLink><relatesTo>1</relatesTo><i> sh.toibaeva@aues.kz</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Electrical+%26+Computer+Engineering+%282088-8708%29%22">International Journal of Electrical & Computer Engineering (2088-8708)</searchLink>. Aug2025, Vol. 15 Issue 4, p4031-4042. 12p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Formal+languages%22">Formal languages</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+neural+networks%22">Artificial neural networks</searchLink><br /><searchLink fieldCode="DE" term="%22Automation%22">Automation</searchLink><br /><searchLink fieldCode="DE" term="%22Total+quality+management%22">Total quality management</searchLink><br /><searchLink fieldCode="DE" term="%22Sustainability%22">Sustainability</searchLink><br /><searchLink fieldCode="DE" term="%22Regulatory+compliance%22">Regulatory compliance</searchLink><br /><searchLink fieldCode="DE" term="%22Information+networks%22">Information networks</searchLink><br /><searchLink fieldCode="DE" term="%22Sustainable+development%22">Sustainable development</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: This paper explores the integration of formal languages and neural networks into quality management systems to enhance efficiency and sustainability. Formal languages standardize regulatory documents, reducing misinterpretation and simplifying modification, contributing to innovative infrastructure (SDG 9). Recurrent neural networks (RNNs) automate document analysis, non-conformance detection, and decision-making, improving production efficiency and promoting responsible consumption (SDG 12). Automation in quality management reduces costs, enhances competitiveness, and aligns with decent work and economic growth (SDG 8). Standardizing documentation and automating quality control enhance workforce competencies and support quality education (SDG 4). These technologies strengthen regulatory transparency, reduce legal risks, and improve governance, supporting strong institutions (SDG 16). The proposed approach fosters sustainable development through digitalization and automation, ensuring efficiency, innovation, and compliance with environmental and social standards. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of International Journal of Electrical & Computer Engineering (2088-8708) is the property of Institute of Advanced Engineering & Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.11591/ijece.v15i4.pp4031-4042 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 12 StartPage: 4031 Subjects: – SubjectFull: Formal languages Type: general – SubjectFull: Artificial neural networks Type: general – SubjectFull: Automation Type: general – SubjectFull: Total quality management Type: general – SubjectFull: Sustainability Type: general – SubjectFull: Regulatory compliance Type: general – SubjectFull: Information networks Type: general – SubjectFull: Sustainable development Type: general Titles: – TitleFull: Modernizing quality management with formal languages and neural networks. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Utepbergenov, Irbulat – PersonEntity: Name: NameFull: Toibayeva, Shara IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 08 Text: Aug2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 20888708 Numbering: – Type: volume Value: 15 – Type: issue Value: 4 Titles: – TitleFull: International Journal of Electrical & Computer Engineering (2088-8708) Type: main |
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